Honest Signals: How They Shape Our World

By Alex Pentland. 2008

612 citations recorded by the source corpus.

Subfields: Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/68cf46020b94c5e4cd155fed46a7348ed1b1b7f4

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In Statistical and Nonlinear Physics

Citations in the corpus

High-Resolution Measurements of Face-to-Face Contact Patterns in a Primary School (2011, background): “Recent advances in distributed sensing systems, based on mobile devices and wearable sensors, provide new ways of gathering data on human contacts and allow to mine the proximity relations and close-range interactions of individuals in real-world large-scale settings [3,11-17].”
Dynamics of Person-to-Person Interactions from Distributed RFID Sensor Networks (2008, background): “On the other side of the spectrum, the MIT Reality Mining project [10,11,18] collected rich multichannel data on face-to-face interactions at the expense of deploying sophisticated ‘‘sociometric badges’’.”
Age Trends in Daily Social Contact Patterns (2011, background): “Recent advances in data collection techniques may make such data more accessible, including the development of devices that collect real-time data on patterns of interpersonal contact and speech (Pentland 2008) and other wearable devices that passively collect information about activity levels, hear”
Charisma as signal: An evolutionary perspective on charismatic leadership (2017, background): “…signal information simply by expending greater amounts of energy to attract the attention of others – for example, one of the most effective ways to direct group movement might be simply pointing excitedly toward a source of food or a potential aggressor (surgency; Pentland & Heibeck, 2010).”
Finding your friends and following them to where you are (2012, background): “For instance, behavioral patterns of people taking taxis, rating movies, choosing cell phone providers, or sharing music are often best predicted by the habits of related people, rather than by the attributes of the individual such as age, ethnicity, or education [3, 24].”
Plink: "Thin Slices" of Music (2010, background): “Many other studies have been conducted since seeking to determine what kinds of social judgments can be made and on what basis (see, for example, Kraus & Keltner, 2009; Pentland, 2008).”
Rebooting Psychotherapy Research and Practice to Reduce the Burden of Mental Illness (2011, methodology): “Electronic devices to record functioning in everyday life are already in use in such areas as the study of sleep, mood, social interaction, and speech (e.g., Hasler, Mehl, Bootzin, & Vazire, 2008; Pentland, 2008).”
Contact Patterns in a High School: A Comparison between Data Collected Using Wearable Sensors, Contact Diaries and Friendship Surveys (2015, background): “[17] Pentland A (2008) Honest signals: how they shape our world.”
Contact Patterns among High School Students (2014, background): “The research community has moreover started to systematically take advantage of recent technological advances to move from methods ranging from diaries and surveys [4–13] to new technologies based on wearable sensors able to detect close proximity [13–18] and even face-toface contacts of individuals”
Digital Epidemiology (2012, background): “Analogously, advances in wearable devices have radically improved our capability to track human contacts at high spatial and temporal resolution [22], affording a much more detailed characterization and understanding of social behaviors [23], complementing previous work based on large-scale surveys ”
EmotionSense: a mobile phones based adaptive platform for experimental social psychology research (2010, background): “In the past years, we have witnessed an increasing interest in the use of ubiquitous technologies for measuring and monitoring user behavior [24].”
Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? (2011, background): “Mobile phones, vehicles, factory automation systems, and other devices are routinely instrumented to generate streams of data on their activities, making possible an emerging field of “reality mining” (Pentland and Pentland 2008).”
What's in a crowd? Analysis of face-to-face behavioral networks (2010, background): “Bluetooth and Wifi technologies give access to proximity patterns [22–26], and even face-to-face presence can be resolved with high spatial and temporal resolution [27–30].”
Measuring Large-Scale Social Networks with High Resolution (2014, background): “To gain a fuller view of participants’ behavior, some CSS studies have developed an approach of employing Radio Frequency Identification (RFID) devices [12], sociometetric badges [13,14], as well as smartphones for the data collection [15–18].”
Social signal processing: Survey of an emerging domain (2009, background): “However, in some cases gestures are performed unconsciously and they are interesting from an SSP point of view because they account for honest information [146], i.”
Automatic nonverbal analysis of social interaction in small groups: A review (2009, background): “With a few exceptions – which have been chosen as they have a clear relation to the small group case – the paper does not discuss cases of research in nonverbal modeling of dyadic conversations (e.g. [103]) or of large groups (e.g. [29]), which deserve a separate treatment.”
Bridging the Gap between Social Animal and Unsocial Machine: A Survey of Social Signal Processing (2012, neutral): “These are " honest signals " [48] since they cannot be faked or simulated: a particular type of informative signals.”